Wireless networks rely on a large number of individual base stations or cells to provide high capacity wireless services over large coverage areas, such as market areas (e.g., cities), surrounding residential areas (e.g., suburbs, counties), highway corridors and rural areas. Continuous radio connectivity across these large coverage areas is accomplished via user mobility from one base station to others as the user traverses the network's operating area. High reliability mobility in mobile wireless networks minimizes the number of dropped calls or other abnormal discontinuations of radio service to the supported users.
In order to maintain high reliability, a network manages neighbor lists, such as Neighbor Relations Tables, that define, for any given base station within the network, nearby network base stations that are likely or desired candidates for mobility handover. Therefore, accurate and well-optimized neighbor lists support a high network performance, as utilization of neighbor lists reduces the incidence of dropped calls and failed handovers between network cells.
Traditionally, neighbor lists have been manually optimized by network operations staff, although recent technologies have been developed that are capable of performing ongoing automated optimizations of neighbor lists within networks. For example, existing methods for Automatic Neighbor Relations based optimization (ANR) utilize common rules applied to all network cells, such as rules that define when to add, drop, reprioritize, and/or prohibit an addition of cells to a specific or target cell's neighbor list. These methods (e.g., methods which utilize handover counts or detected set reporting) provide a basic set of rules for automatically maintaining neighbor lists. However, such reliance on basic, shared ANR optimization often leads to poor or undesired performance in real world networks, such as networks with complex radio frequency propagation environments.